OpenCode plugin that optimizes token usage by pruning obsolete tool outputs from conversation context
npm install @keakon/opencode-dcp
Automatically reduces token usage in OpenCode by removing obsolete tools from conversation history.
Add to your OpenCode config:
``jsonc`
// opencode.jsonc
{
"plugin": ["@keakon/opencode-dcp@latest"],
}
Using @latest ensures you always get the newest version automatically when OpenCode starts.
Restart OpenCode. The plugin will automatically start optimizing your sessions.
DCP uses multiple tools and strategies to reduce context size:
Discard — Exposes a discard tool that the AI can call to remove completed or noisy tool content from context.
Extract — Exposes an extract tool that the AI can call to distill valuable context into concise summaries before removing the tool content.
Deduplication — Identifies repeated tool calls (e.g., reading the same file multiple times) and keeps only the most recent output. Runs automatically on every request with zero LLM cost.
Supersede Writes — Prunes write tool inputs for files that have subsequently been read. When a file is written and later read, the original write content becomes redundant since the current file state is captured in the read result. Runs automatically on every request with zero LLM cost.
Purge Errors — Prunes tool inputs for tools that returned errors after a configurable number of turns (default: 4). Error messages are preserved for context, but the potentially large input content is removed. Runs automatically on every request with zero LLM cost.
Your session history is never modified—DCP replaces pruned content with placeholders before sending requests to your LLM.
LLM providers like Anthropic and OpenAI cache prompts based on exact prefix matching. When DCP prunes a tool output, it changes the message content, which invalidates cached prefixes from that point forward.
Trade-off: You lose some cache read benefits but gain larger token savings from reduced context size and performance improvements through reduced context poisoning. In most cases, the token savings outweigh the cache miss cost—especially in long sessions where context bloat becomes significant.
> Note: In testing, cache hit rates were approximately 65% with DCP enabled vs 85% without.
Best use case: Providers that count usage in requests, such as Github Copilot and Google Antigravity have no negative price impact.
DCP uses its own config file:
- Global: ~/.config/opencode/dcp.jsonc (or dcp.json), created automatically on first run$OPENCODE_CONFIG_DIR/dcp.jsonc
- Custom config directory: (or dcp.json), if OPENCODE_CONFIG_DIR is set.opencode/dcp.jsonc
- Project: (or dcp.json) in your project’s .opencode directory
Default Configuration (click to expand)
`jsonc`
{
"$schema": "https://raw.githubusercontent.com/Keakon/opencode-dynamic-context-pruning/master/dcp.schema.json",
// Enable or disable the plugin
"enabled": true,
// Enable debug logging to ~/.config/opencode/logs/dcp/
"debug": false,
// Notification display: "off", "minimal", or "detailed"
"pruneNotification": "detailed",
// Slash commands configuration
"commands": {
"enabled": true,
// Additional tools to protect from pruning via commands (e.g., /dcp sweep)
"protectedTools": [],
},
// Protect from pruning for
"turnProtection": {
"enabled": false,
"turns": 4,
},
// Protect file operations from pruning via glob patterns
// Patterns match tool parameters.filePath (e.g. read/write/edit)
"protectedFilePatterns": [],
// LLM-driven context pruning tools
"tools": {
// Shared settings for all prune tools
"settings": {
// Nudge the LLM to use prune tools (every
"nudgeEnabled": true,
"nudgeFrequency": 10,
// Additional tools to protect from pruning
"protectedTools": [],
},
// Removes tool content from context without preservation (for completed tasks or noise)
"discard": {
"enabled": true,
},
// Distills key findings into preserved knowledge before removing raw content
"extract": {
"enabled": true,
// Show distillation content as an ignored message notification
"showDistillation": false,
},
},
// Automatic pruning strategies
"strategies": {
// Remove duplicate tool calls (same tool with same arguments)
"deduplication": {
"enabled": true,
// Additional tools to protect from pruning
"protectedTools": [],
},
// Prune write tool inputs when the file has been subsequently read
"supersedeWrites": {
"enabled": true,
},
// Prune tool inputs for errored tools after X turns
"purgeErrors": {
"enabled": true,
// Number of turns before errored tool inputs are pruned
"turns": 4,
// Additional tools to protect from pruning
"protectedTools": [],
},
},
}
DCP provides a /dcp slash command:
- /dcp — Shows available DCP commands/dcp context
- — Shows a breakdown of your current session's token usage by category (system, user, assistant, tools, etc.) and how much has been saved through pruning./dcp stats
- — Shows cumulative pruning statistics across all sessions./dcp sweep
- — Prunes all tools since the last user message. Accepts an optional count: /dcp sweep 10 prunes the last 10 tools. Respects commands.protectedTools.
When enabled, turn protection prevents tool outputs from being pruned for a configurable number of message turns. This gives the AI time to reference recent tool outputs before they become prunable. Applies to both discard and extract tools, as well as automatic strategies.
By default, these tools are always protected from pruning across all strategies:
task, todowrite, todoread, discard, extract, batch, write, edit
The protectedTools arrays in each section add to this default list.
Settings are merged in order:
Defaults → Global (~/.config/opencode/dcp.jsonc) → Config Dir ($OPENCODE_CONFIG_DIR/dcp.jsonc) → Project (.opencode/dcp.jsonc`).
Each level overrides the previous, so project settings take priority over config-dir and global, which take priority over defaults.
Restart OpenCode after making config changes.
Subagents — DCP is disabled for subagents. Subagents are not designed to be token efficient; what matters is that the final message returned to the main agent is a concise summary of findings. DCP's pruning could interfere with this summarization behavior.
MIT